Major Release v0.6
Highlights:
- DTM: Added a basic dynamic topic modeling technique based on the global c-TF-IDF representation
model.topics_over_time(docs, timestamps, global_tuning=True)
- DTM: Option to evolve topics based on t-1 c-TF-IDF representation which results in evolving topics over time
- Only uses topics at t-1 and skips evolution if there is a gap
model.topics_over_time(docs, timestamps, evolution_tuning=True)
- DTM: Function to visualize topics over time
model.visualize_topics_over_time(topics_over_time)
- DTM: Add binning of timestamps
model.topics_over_time(docs, timestamps, nr_bins=10)
- Add function get general information about topics (id, frequency, name, etc.)
get_topic_info()
- Improved stability of c-TF-IDF by taking the average number of words across all topics instead of the number of documents
Fixes: